A real-time diagnostics pipeline may allow for reduce resolution time for service degradations in large-scale services. In some situations, performance, monitoring, and diagnostics of thousands of servers and millions of users interacting with the service from multiple geographies becomes extremely challenging. For example, identifying issues in real time to pin point the issue vectors and act upon them in real time is necessary to prevent service degradation. Conventional systems rely on distributed batch processing systems and are typically not online systems suitable self-rich enough to pin point scale and performance bottlenecks in real time. Furthermore, these systems do not provide rich enough forensics to pin point where the issue is. For example, conventional systems can identify that CPU usage is spiking but cannot provide details into what process is causing the CPU to spike.